M. Indirani*, S. Shankar
Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1657-1674, 2023, DOI:10.32604/iasc.2023.026148
Abstract Recent developments in computer vision applications have enabled detection of significant visual objects in video streams. Studies quoted in literature have detected objects from video streams using Spatiotemporal Particle Swarm Optimization (SPSOM) and Incremental Deep Convolution Neural Networks (IDCNN) for detecting multiple objects. However, the study considered optical flows resulting in assessing motion contrasts. Existing methods have issue with accuracy and error rates in motion contrast detection. Hence, the overall object detection performance is reduced significantly. Thus, consideration of object motions in videos efficiently is a critical issue to be solved. To overcome the above mentioned problems, this research work… More >
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